Download Structural analysis of histamine receptors and its application in drug

Structural analysis of histamine receptors and
its application in drug design
PhD theses
Róbert Kiss
Semmelweis University
PhD School of Pharmaceutical Sciences
Tutor: Dr. Miklós Józan, Ph.D.
Official reviewers: Dr. György Ferenczy, Ph.D.
Dr. Pál Tapolcsányi, Ph.D.
Head of final examination board:
Members of the final examination:
Dr. Tamás Török, D.Sc.
Dr. György Kéri, D.Sc.
Dr. István Kolossváry, D.Sc.
Budapest
2008
1 Introduction
The immune system plays an essential role in the homeostasis. In
allergic diseases, however, the immune system recognizes harmless
antigens as causative agents. Since the number of people suffering
from allergy increases gradually, there is an unmet need for new,
more potent antiallergic agents. Literature data suggest that histamine
H1 and H4 receptors are potential therapeutic targets against allergy.
H1 and H4 antagonists may be used separately or in combination
representing an effective therapeutic option for allergy and other
immunological diseases.
Currently, experimentally determined 3D structure of the
histamine receptors is not available. On the other hand, homology
models can be built by using the experimental 3D structure of a
sequentially related protein, and the sequence alignment of the target
and the template proteins.
Structure-based methods can be used effectively in several stages
of drug design. For example, a structural protein model can be used
to map the binding site, and explore novel sites for ligand design.
These sites may provide opportunities increasing affinity and/or
selectivity. Moreover, protein models of high quality can be used to
identify novel ligands by virtual screening. In this case, promising
compounds are selected from large databases by high throughput
docking and the activity of these compounds is tested using in vitro
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biological assays. In vitro hits can serve as suitable starting points for
the development of novel, potent and selective ligands.
2 Objectives
We aimed to develop a relevant homology model of the human
histamine H1 receptor (hH1R). We planned to use site-directed
mutagenesis data from the literature to identify the binding site of the
receptor. Furthermore, we aimed to dock known H1 antagonists to
the binding site of the receptor. We proposed that we can identify
novel interaction sites of the binding site by the analysis of the
resulting ligand-receptor complexes.
We also aimed to develop a homology model of the human
histamine H4 receptor (hH4R). After the identification of the binding
site, we planned to dock known H4 actives to our receptor model.
Then we aimed to analyze the applicability of hH4R models
developed with different methodologies for virtual screening.
Furthermore, our objective was performing a virtual screening on
one of the developed hH4R models. For this purpose we collected
more than 8.7 million compounds that were commercially available.
After the virtual screening, we planned to test the H4 activity of the
most promising compounds by biological tests.
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3 Methods
Automatic sequence alignment was carried out by ClustalW 1.83.
Homology models of hH1R and hH4R were built by MODELLER.
As a template, we used the crystal structure of bovine rhodopsin
determined in 2000 (PDB ID: 1F88). The models were validated by
the available mutagenesis data from literature and by a set of
structural validation programs (PROCHECK, WHATIF, PROSA,
HARMONY). Ligand docking with flexible protein side chains was
carried out by FlexiDock. FlexX was used for docking with rigid
protein side chains. High throughput docking on the hH4R model
was exclusively done using the “ClusterGrid” production grid system
developed by the National Information Infrastructure Development
Institute (NIIF). Binding poses were scored by the own score of
FlexX as well as the scoring functions available in the CScore
package (Sybyl). The H4 activity of the virtual hits were evaluated
by radioligand binding assay on a SK-N-MC cell line stably
transfected with hH4R.
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4 Results
4.1 The human histamine H1 receptor (hH1R) model
4.1.1 Agonist binding and receptor activation
According to the available mutational data Asp107 (3.32) and
Asn198 (5.46) have crucial roles in histamine binding, while Lys191
(5.39) is mainly responsible for receptor activation. We found that
Asp107 (3.32) and Asn198 (5.46) are in favorable positions for
anchoring histamine. On the other hand, Lys191 (5.39) is not able to
form an H-bond with the imidazole N(1) of histamine. We speculate
that after histamine binding Lys191 (5.39) can approach TM3.
Consequently, the EC part of TM5 moves to the interior of the
receptor, while the IC part, that is the G-protein binding site of
hH1R, moves in the opposite direction. This can result in the
activation of the receptor (Figure 1).
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Figure 1. Proposed repositioning of TM5 in hH1R after histamine
binding.
4.1.2 Identification of novel interaction sites for antagonist binding
Mutational data suggest a crucial role for Asp107 (3.32), Trp158
(4.56), Phe432 (6.52) and Phe435 (6.55) in antagonist binding.
According to our model, we established that these residues are in
favorable position to form interactions with ligands. We identified
several novel amino acids at the binding site: Tyr108 (3.33), Phe184
(5.32), Phe190 (5.38), Phe199 (5.47), Phe424 (6.44), Trp428 (6.48)
and Tyr431 (6.51). The role of these residues in ligand binding was
not described in the literature so far.
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4.1.3 Binding mode analysis of known H1 antagonists
Four
known
H1
antagonists
(mepyramine,
acrivastine,
desloratadine, loratadine) were docked successfully to the binding
site of the hH1R model by FlexiDock. Acrivastine, a second
generation, zwitterionic antihistamine formed two ionic interactions
with the side chains of Asp107 (3.32) and Lys191 (5.39) (Figure 2).
Figure 2. Proposed binding mode of acrivastine at the hH1R binding
site.
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4.2 The human histamine H4 receptor (hH4R) model
4.2.1 Agonist binding and receptor activation
Based
on
docking
calculations,
ligand-receptor
complex
optimizations and analyses of interacting molecular surfaces
combined with experimental data from Shin et al. we identified a
novel binding mode of histamine In this binding mode, differing
significatly from that previously reported, the protonated ethylamine
side chain and imidazole N(3)-H group of histamine form
interactions with the side chains of Glu182 (5.46) and Asp94 (3.32),
respectively (Figure 3).
Figure 3. Proposed binding mode of histamine at the hH4R binding site.
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We found that two agonists (histamine and OUP-16) form
complementary interactions with Asp94 (3.32), Glu182 (5.46) and
Thr323 (6.55), whereas JNJ7777120 interacts with Asp94 (3.32) and
Glu182 (5.46) only.
4.2.2 Enrichment tests
We analyzed the applicability of six hH4R models developed by
different methodologies for virtual screening by enrichment tests. We
found that different inactive sets have only marginal effect on the
highest achievable enrichment factors. On the other hand, the ligand
used for optimizing the receptor model, the pharmacophore
constraints and the different scoring functions applied in high
throughput docking had all significant effect on the results.
4.2.3 Virtual screening
The database containing 8.7 million 3D-structures of small
molecules was screened virtually on one of the developed hH4R
models by FlexX. After the virtual screening we selected compounds
for in vitro testing by two different methods using visual inspection
and automatic filtering. In summary, 255 virtual hits were evaluated
by radioligand binding assay. We identified sixteen compounds with
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significant H4 activity representing an overall hit rate of 6.3 %.
(Figure 4).
Figure 4. Distribution of the activities of the in vitro hits.
5 Conclusions
1.
We have developed the structural model of hH1R by homology
modeling. We analyzed the role of amino acids at the binding
site that were proved to take part in agonist or antagonist
binding. We identified several aromatic residues (Tyr108
(3.33), Phe184 (5.32), Phe190 (5.38), Phe199 (5.47), Phe424
(6.44), Trp428 (6.48), Tyr431 (6.51)) in suitable positions for
antagonist binding. These novel interaction sites can be
exploited in the design of new H1 antagonists.
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2.
We built the homology model of hH4R that were refined with
considering ligand informations, docking and subsequent
optimization. After the docking and optimization we found that
two H4 agonists (histamine, OUP-16) form interactions with
Asp94 (3.32) and Glu182 (5.46) as well as Thr323 (6.55). On
the other hand, the H4 antagonist JNJ-7777120 forms
interactions with Asp94 (3.32) and Glu182 (5.46) only. We
demonstrated that histamine binds to hH4R in a different
conformation that was previously proposed in the literature.
Further investigations are needed to confirm this novel binding
mode as well as the role of Thr323 (6.55) in ligand binding and
receptor activation.
3.
Six different hH4R models were evaluated by enrichment tests
using twentyfive different scoring function combinations and
three inactive molecule sets. We found that ligand information
can significantly influence the performance of the models in
virtual screenings. On the other hand, the application of
different inactive sets did not considerably affect the maximal
achievable enrichment factors. According to the calculated
enrichment factors some of our hH4R models are suitable for
virtual screening, and therefore can be used to identify novel
H4 ligands.
4.
We carried out a virtual screening on one of our hH4R models
by docking more than 8.7 million 3D-structures of small
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molecules. To the best of our knowledge, this is one of the
largest structure-based virtual screenings, where the virtual hits
were confirmed by an in vitro assay. Moreover, this is the first
structure-based drug design study reported on the hH4R. After
the virtual screening, we identified several novel ligands with
significant H4 affinity. These scaffolds can serve as starting
points in the development of potent and selective H4 ligands in
future.
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Basic publications related to the theme of the PhD thesis
Kiss, R.; Kovári, Z.; Keserű, G. M. Homology modelling and binding site
mapping of the human histamine H1 receptor. Eur. J. Med. Chem. 2004,
39, 959-967.
Kiss, R.; Noszál, B.; Rácz, Á.; Falus, A.; Erős, D.; Keserű, G. M. Binding
mode analysis and enrichment studies on homology models of the human
histamine H4 receptor. Eur. J. Med. Chem. 2008, 43, 1059-1070.
Kiss, R.; Kiss, B.; Könczöl, Á.; Szalai, F.; Jelinek, I.; László, V.; Noszál,
B.; Falus, A.; Keserű, G. M. Discovery of Novel Human Histamine H4
Receptor Ligands by Large-Scale Structure-based Virtual Screening. J.
Med. Chem. 2008, 51, 3145-3153.
Other publication related to the theme of the PhD thesis
Jójárt, B.; Kiss, R.; Viskolcz, B.; Keserű, G. M. Activation Mechanism of
the Human Histamine H4 Receptor – An Explicit Membrane Molecular
Dynamics Simulation Study. J. Chem. Inf. Model. 2008, 48, 1199-1210.
Publications related to the other themes
Erős, D.; Szántai-Kis, C.; Kiss, R.; Kéri, G.; Hegymegi-Barakonyi, B.;
Kövesdi, I.; Őrfi, L. Structure-activity relationships of PDE5 inhibitors.
Curr. Med. Chem. 2008, 15, 1570-1585.
Várkondi, E.; Pintér, F.; Kiss, R.; Schwab, R.; Breza, N.; Őrfi, L.; Kéri, G.;
Peták, I. Biochemical assay-based selectivity profiling of clinically relevant
kinase inhibitors on mutant forms of EGF receptor. J. Recept. Signal
Transduct. Res. 2008, 28, 295-306.
Hegymegi-Barakonyi, B.; Székely, R.; Varga, Z.; Kiss, R.; Borbélya, G.;
Németh, P.; Bánhegyi, J.; Pató, Z.; Greff, Z.; Horváth, G.; Mészáros, J.;
Marosfalvi, D.; Erős, D.; Szántai-Kis, Cs.; Breza, S.; Garavaglia, S.;
Perozzi, S.; Rizzi, M.; Hafenbradl, D.; Ko, M.; Av-Gay, Y.; Klebl, B. M.;
Őrfi, L.; Kéri, G. Signalling inhibitors against Mycobacterium tuberculosis
– early days of a new therapeutic concept in tuberculosis Curr. Med. Chem.
(under review)
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